Robert A. Beckman

The paper develops a probability distribution for rare subclones in cancer and applies it to simulate dynamic precision medicine to improve treatment outcomes despite sequencing limitations.

This study enhances a personalized cancer treatment strategy by incorporating both irreversible and reversible drug resistance mechanisms, showing improved patient outcomes compared to current approaches.

The paper develops two in vitro models of endocrine therapy-resistant HER2+/ER+ breast cancer and identifies lipid metabolism and ferroptosis as therapeutic vulnerabilities.

CDGnet recommends targeted cancer therapies using a network approach that integrates biological pathway information and patient-specific molecular data.